Date: Mon, 02 Dec 1996 16:01:01 GMT
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<TITLE>CSE 473 TOPICS FOR FINAL EXAM</TITLE>
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<H1>CSE 473 Topic List for the Final Exam<br>
</h1> 

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<H2>
Common Lisp: Evaluation of S-expressions involving</H2>
<ol>
<li>   CONS, LIST, APPEND, LET, FIRST, REST, +, *, NULL, =,
<li>   SETF, APPLY, QUOTE, DEFUN, IF, PROGN, LAMBDA
</ol>

<H2>Production systems and pattern matching</H2>
<ol>
<li>   Unordered and ordered production systems
<li>   Discrimination nets
</ol>

<H2>Knowledge representation</H2>
<ol>
<li>   ISA Hierarchies and Partial Orders
<li>   Propositional Calculus
   Truth tables, rules of inference
<li>   Predicate Calculus
<li>    Well-formed formulas
<li>    Semantics: Interpretations and models
<li>    Quantification and representation of unique existence
</ol>

<H2>State-space search</H2>
<ol>
<li>   Computing the size of the state space for the painted squares puzzle
<li>   Iterative formulation of depth-first search
<li>   Breadth-first search, best-first search, uniform-cost search
<li>   A* search algorithm, with f'(n) = g'(n) + h'(n)
<li>   Genetic search
</ol>

<H2>Logical reasoning</H2>
<ol>
<li>   Proofs in the propositional calculus by 
    perfect induction
<li>   Resolution in the propositional calculus
<li>   Satisfiability, Tautology and Contradiction in
    the propositional calculus
<li>   Predicate calculus literals and clauses
<li>   Reduction to clause form
<li>   Unification, most general unifiers
<li>   Predicate calculus resolution
<li>   Satisfiability, tautology and contradiction in
    the predicate calculus
</ol>

<H2>Probabilistic reasoning</H2>
<ol>
<li>   Bayes rule
<li>   Odds
</ol>

<H2>Commonsense reasoning</H2>
<ol>
<li>   Case-based reasoning approach to problem solving
<li>   Distance functions and distance metrics
</ol>

<H2>Planning</H2>
<ol>
<li>   Difference between world space and plan space
<li>   Iterative-deepening depth-first search
</ol>

<H2>Learning</H2>
<ol>
<li>   Learning as improvement as measured by a function of merit, etc.
<li>   Concept synthesis in theory formation, example of prime numbers in AM
</ol>

<H2>Natural-language understanding</H2>
<ol>
<li>   Levels of NLU from acoustic to pragmatic
<li>   Semantic grammar
</ol>

<H2>Vision</H2>
<ol>
<li>   Edge detection with the Roberts cross operator
<li>   Representing contours with chain codes
<li>   Hough transform (how it works and its main formula)
<li>   Medial axis transform ("skeleton")
<li>   Ramer's algorithm for polygonal approximation
<li>   Guzman's method for labelling a line drawing of blocks
</ol>

<H2>Neural networks</H2>
<ol>
<li>   Perceptrons
<li>   Fundamental training theorem for perceptrons
</ol>






<p>


<HR>
<address>
tanimoto@cs.washington.edu
</address>

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